Time signal analysis and derivation of scale factors

ABSTRACT

Analyzing an analysis time signal that has been generated from encoding and decoding and original time signal according to an encoding algorithm. The encoding block raster underlying the analysis time signal used by the encoding algorithm is determined. The analysis time signal is converted from its timely representation of analysis spectral coefficients to a spectral representation by using the established encoding block raster. At least two analysis spectral coefficients are grouped. The greatest common divisor of the analysis spectral coefficients are calculated, corresponding to the quantization step width used when quantizing the encoding algorithm or an integer multiple of it. In the case of an audio signal, the scale factor can easily be established for this group of spectral coefficients, i.e., for a scale factor band, from the quantization step width. All parameters used for the quantization of the original time signal are known; full iteration loops need not be performed.

FIELD OF THE INVENTION

The present invention refers to the analysis of signals encoded andre-decoded in any way, and particularly to analyzing an analysis timesignal comprising audio and/or video data generated by encoding anddecoding of an original time signal according to an encoding algorithm.

BACKGROUND OF THE INVENTION AND PRIOR ART

It is generally known to encode audio and/or video signals by using acertain encoding method to obtain an encoded version of the originaltime signal, wherein the encoded version of the original time signalshould differ basically from the original time signal in that the amountof data of the encoded signal is smaller than the amount of data of theoriginal time signal. In such a case, the encoding algorithm forobtaining the encoded signal from the original signal and also thedecoding algorithm that is essentially a reversal of the encodingalgorithm referred to as a data reduced encoding algorithm.

Different encoding algorithms exists for data reduction of audiosignals, which are subject of a series of international standards,wherein the encoding algorithm MPEG-2 AAC, for example, is described indetail in the international standard ISO/IEC 13818-7.

In the following, reference will be made to FIG. 8, which shows a blockdiagram of a MPEG audio encoding method. Such an audio encoder typicallycomprises an audio input 70, where a stream of time discrete samples isfed in, that are PCM samples, for example, that are 16 bit wide, forexample. In an analysis filter bank 71, the stream of time discreteaudio samples is divided into encoding blocks or frames of samples,windowed by using a respective window function and then converted into aspectral representation, for example by a filter bank or by a Fouriertransform or a variation of the Fourier transform, such as a modifieddiscrete cosine transform (MDCT). Thus, subsequent encoding blocks orframes of spectral coefficients are present at the output of theanalysis filter bank 71, wherein a block of spectral coefficients is thespectrum of an encoding block of audio samples. Often, a 50% overlappingof subsequent encoding blocks is used, so that one window of, forexample, 2048 audio samples is viewed per block, and by this processing1024 new spectral coefficients will be generated.

The time discrete audio signal at input 70 will further be fed into apsychoacoustic model 72 to obtain a data reduction, such that, as isknown, the masking threshold of the audio signal will be calculateddepending on the frequency to perform a quantization of the spectralcoefficients in a block 73 denoted with quantization and encoding, whichdepends on the masking threshold.

In other words, quantizing the spectral coefficients will be performedso coarsely, that the quantization noise introduced thereby lies belowthe psychoacoustic masking threshold, which is calculated by thepsychoacoustic model 72, so that the quantization noise is ideallyinaudible. This procedure causes that typically a certain number ofspectral coefficients that are unequal to 0 at the output of theanalysis filter bank 71 will be set to 0 after quantization, since thepsychoacoustic model 72 has established that they will be masked byadjacent spectral coefficients and are therefore inaudible.

After quantizing a spectral representation of the encoding block of timediscrete samples is present, wherein the quantization noise is, ifpossible, below the psychoacoustic masking threshold. These data reducedquantized spectral values can then be encoded without any loss,depending on the encoder that will be used, by using an entropyencoding, for example a Huffman encoding. Thereby, a stream of codewords will be obtained, to which side information needed by a decoderwill be added in a bit stream multiplexer 74, such as informationregarding the analysis filter bank, information regarding thequantization, such as scale factors, or side information regardingfurther function blocks. Such further function blocks are in MPEG-2-AACfor example TNS processing, intensity stereo processing, center/sidestereo processing or a prediction from spectrum to spectrum.

At an output 75 of the encoder, also referred to as bit stream output,the signal encoded according to the encoding algorithm shown in FIG. 8will be present blockwise.

In the case of the decoder, the encoded signal will be fed into a bitstream input 80 of a decoder shown in FIG. 9, at the output 75 of theencoder shown in FIG. 8, which first carries out a bit streamdemultiplex operation in a block 81 denoted as a bit streamdemultiplexer, to separate the spectral data from the side information.At the output of block 81 then the code words will be present again,which represent the individual spectral coefficients. By using arespective table, the code words will be decoded to obtain quantizedspectral values. These quantized spectral values will then be processedin a block 82 denoted with “inverse quantization” to recalculate thequantization introduced in block 73 (FIG. 8). At the output of block 82,dequantized spectral coefficients will be present, which will now beconverted into the time domain via a synthesis filter bank 83, workinginverse to a analysis filter bank 71 (FIG. 8), to obtain the decodedsignal at an audio output 84.

When considering the encoding/decoding concept illustrated in FIGS. 8and 9, it becomes clear that this is a block-oriented method, whereinthe block generation is caused by the analysis filter bank block 71 ofFIG. 8, and wherein the block forming will only be cancelled at theaudio output 84 of the decoder shown in FIG. 9.

It further becomes clear, that this is a lossy encoding concept, sincethe decoded signal present the audio output 84 generally comprises lessinformation than the original time signal present at the audio input 70.By the quantizer 73, controlled by the psychoacoustic model 72,information will be removed from the original time signal present at theaudio input 70, which will not be added again in the decoder, but willbe abandoned. Subjectively, this abandonment of information does,however, not lead to any quality losses in the ideal case, due to thepsychoacoustic model 72 that is adapted to the human hearing properties,but merely to a wanted data compression.

Here, it should be noted, that the encoding concept described in FIG. 8and FIG. 9 with the example of an audio signal, will be usedcorrespondingly for image or video signals, wherein instead of thetimely audio signal a video signal is present, wherein the spectralrepresentation is no audio-frequency spectrum, but a location spectrum.Otherwise, an analysis filter bank or transform, respectively, a psychooptic model, a thereby controlled quantization and entropy encoding alsotake place in the video signal compression, wherein the wholeencoding/decoding concept also runs blockwise.

The decoded signal (in the example of FIG. 9 the decoded audio signal atthe audio output 84) is typically again a stream of time discretesamples based on an encoding block raster that is, however, generally,not visible in the decoded signal, except when special measures aretaken.

While the process of the decoding is the normal case in the application,namely the transmission and storage of audio and/or image signals, thereare, however, cases where it is of interest to “retranslate” a givendecoded signal into a bit stream representation. This is especially ofinterest in the following cases, when only the decoded signal isavailable.

On the one hand, there is often a need to examine encoding systems withreference to the signals, which are encoded and re-decoded by them, forexample to find out why a still unknown encoder sounds so well.

On the other hand, there is a need in the area of copyright protectionto prove beyond doubt that a piece of music or an image has been encodedoriginally with a certain encoder.

Finally, there is a need in the area of transmission, for example viaseveral networks, to encode a decoded signal again. In this case, theencoder/decoder concept shown in FIG. 8 and FIG. 9 is performed severaltimes subsequently on an original audio time signal. There are problemsin that so-called tandem encoding distortions of subsequent codec stageswill be introduced.

In the specialist publication “NMR Measurements on Multiple GenerationsAudio Coding”, Michael Keyhl, Jürgen Herre, Christian Schmidmer, 96.AES-Meeting, 26^(th) Feb. to 1st Mar. 1994, Amsterdam, Preprint 3803, itis suggested to introduce an identification mark into a decoded signalfor reducing the tandem encoding distortions, subsequent encoder stagesbeing able to access this mark to perform its encoding block division ofthe signal to be encoded/decoded again based on this identificationmark, such that all codec stages in a chain of codec stages use the sameencoding block raster.

Although this method reduces the tandem encoding distortionssignificantly, it is still disadvantageous, in that the identificationmark has to be introduced by a decoder and has to be extracted again andinterpreted by a subsequent encoder. Therefore, changes both at adecoder and at an encoder are necessary. Further, this concept is ofcourse only applicable for a tandem encoding of decoded signals havingthis identification mark for the encoding block raster. For signals thatdo not have this identification mark, a codec stage in a chain of codecstages can, of course, not access an identification mark.

Similar problems or restrictions of the flexibility occur also with theMOLE concept, described in “ISO/MPEG Layer 2—Optimum re-Encoding ofDecoded Audio using a MOLE-Signal”, John Fletcher, 104th AES-Convention,16^(th) to 19^(th) May 1998, Preprint No. 4706. Generally, additionaldata describing in detail, in which way the present decoded audio signalhas been encoded and decoded, are introduced into the decoded audiosignal. These data are referred to as MOLE signal. When the decodedaudio signal has to be re-encoded, a specially designed encoder willextract this MOLE signal from the signal to be encoded, and perform theindividual encoding steps based on this signal.

Similar to the concept of the identification mark, there is also adisadvantage that the decoder decoding an originally encoded time signalfor the first time has to introduce the signal into the decoded audiosignal. Such a decoder is thus different to common standard decoders.Further, an encoder re-encoding a decoded signal will have to extractthe determination signal in order to work correspondingly. Thisso-called second encoder also has to be modified such that it can readand interpret the determination signal. Finally, disadvantageously, thisconcept is also only applicable for decoded signals having such adetermination signal, but not for signals that do not have such adetermination signal.

For the quantization (block 73 in FIG. 8), a significant effort is madein the calculation of scale factors, for example by lying thequantization noise introduced by quantization in a psychoacousticencoder below the psychoacoustic masking threshold of the audio signalat the audio input 70. Thereby, it has to be taken into consideration atthe same time that a certain bit stream rate can be necessary at theoutput. Finally, there is also the general aim to compress the audiosignal as strongly as possible, essentially without deterioration of theaudio quality.

In the international standard MPEG-2 AAC that has already been mentionedin the beginning, one possible quantization method is described inparagraph B.2.7, wherein an expensive iterative method with an outeriteration loop and an inner iteration loop is used to calculate optimumscale factors for each scale factor band and thus the optimumquantization step width for all three conditions.

Thus, calculating the iteration loops for determining the quantizationstep width takes up a significant part of the computing effort whenencoding an audio signal.

When, for example, in the case of tandem encoding, a signal has beenencoded and re-decoded, and will be re-encoded, normally the fullquantization has to be calculated again by using the psychoacousticmodel, the inner iteration loop and the outer iteration loop, even whenthe encoding block raster underlying the signal to be processed isknown. This is in so far unsatisfactory, since the quantizationparameters have already been calculated in the earlier encoding of theoriginal time signal. There are, however, no explicit references in there-decoded signal that can be used in a further encoding in order to dowithout the expensive calculation of scale factors and thus thequantization step width.

SUMMARY OF THE INVENTION

It is the object of the present invention to provide an apparatus and amethod for analyzing an analysis signal.

In accordance with a first aspect of the present invention, this objectis achieved by an apparatus for analyzing a spectral representation ofan analysis signal comprising audio and/or video data that has beengenerated by encoding and decoding of an original signal according to anencoding algorithm, wherein the encoding algorithm has a quantizationstep, wherein the quantization step serves to quantize at least part oforiginal spectral coefficients or of spectral coefficients derived fromthe original spectral coefficients of a spectral representation of theoriginal signal by using a quantization step width, wherein thequantization step of the encoding algorithm includes grouping of theoriginal spectral coefficients into scale factor bands, wherein a scalefactor is assigned to each scale factor band, and wherein thequantization step further comprises weighting the original spectralcoefficients in a scale factor band with an encoding amplificationfactor, wherein the encoding amplification factor is in a predeterminedrelation to a scale factor for the scale factor band, comprising: meansfor grouping analysis spectral coefficients or spectral coefficientsderived from the analysis spectral coefficients of the spectralrepresentation of the analysis signal in scale factor bands; means forat least approximately calculating the greatest common divisor of thegrouped analysis spectral coefficients or the spectral coefficientsderived from the analysis spectral coefficients in a scale factor band,to obtain the quantization step width used in the quantization step forthe analysis spectral coefficients or for the analysis spectralcoefficients derived from the analysis spectral coefficients or aninteger multiple of it; and means for calculating the scale factor forthe scale factor band by evaluating the predetermined relation betweenthe encoding amplification factor and the scale factor dissolved afterthe scale factor, wherein the calculated greatest common divisor isinserted in the predetermined relation instead of the encodingamplification factor.

In accordance with a second aspect of the present invention, this objectis achieved by a method for analyzing a spectral representation of ananalysis signal comprising audio and/or video data that has beengenerated by encoding and decoding an original signal according to anencoding algorithm, wherein the encoding algorithm has a quantizationstep, wherein the quantization step serves to quantize at least part ofthe original spectral coefficients or spectral coefficients derived fromthe original spectral coefficients of the spectral representation of theoriginal signal by using a quantization step width, wherein thequantization step of the encoding algorithm comprises grouping theoriginal spectral coefficients into scale factor bands, wherein a scalefactor is associated to each scale factor band, wherein the quantizationstep further comprises weighting the original spectral coefficients in ascale factor band with an encoding amplification factor, wherein theencoding amplification factor is in a predetermined relation to a scalefactor for the scale factor band, comprising: grouping of analysisspectral coefficients or spectral coefficients derived from the analysisspectral coefficients of the spectral representation of the analysissignals into scale factor bands; at least approximately calculating thegreatest common divisor of the grouped analysis spectral coefficients orthe spectral coefficients derived from the analysis spectralcoefficients in a scale factor band, to obtain the quantization stepwidth used in the quantization step for the analysis spectralcoefficients or for the analysis spectral coefficients derived from theanalysis spectral coefficients or an integer multiple of it; andcalculating the scale factor for the scale factor band by evaluating thepredetermined relation between the encoding amplification factor and thescale factor dissolved after the scale factor, wherein the calculatedgreatest common divisor is inserted into the predetermined relationinstead of the encoding amplification factor.

It is another object of the present invention to provide an apparatusand a method for marking and/or encoding an analysis signal working byusing information obtained by the analysis.

In accordance with a third aspect of the present invention, this objectis achieved by an apparatus for marking an analysis time signal,comprising audio and/or video data that has been generated by encodingand decoding an original time signal according to an encoding algorithm,wherein the encoding algorithm has a conversion step and a quantizationstep, wherein the conversion step serves to generate a spectralrepresentation of the original time signal comprising original spectralcoefficients by using an encoding block raster, and wherein thequantization step serves to quantize at least part of the originalspectral coefficients or the spectral coefficients derived from theoriginal spectral coefficients by using a quantization step width,wherein the quantization step of the encoding algorithm includesgrouping of the original spectral coefficients into scale factor bands,wherein a scale factor is assigned to each scale factor band, andwherein the quantization step further comprises weighting the originalspectral coefficients in a scale factor band with an encodingamplification factor, wherein the encoding amplification factor is in apredetermined relation to a scale factor for the scale factor band,comprising: means for analyzing the analysis time signal, comprising:means for establishing the encoding block raster underlying the analysistime signal; means for converting the analysis time signal into aspectral representation of the analysis time signal by using theestablished encoding block raster, wherein the spectral representationof the analysis time signal comprises analysis spectral coefficients;means for grouping of analysis spectral coefficients or spectralcoefficients derived from the analysis spectral coefficients; and meansfor at least approximately calculating the greatest common divisor ofthe grouped analysis spectral coefficients or the spectral coefficientsderived from the analysis spectral coefficients in a scale factor bandto obtain the quantization step width used in the quantization step forthe analysis spectral coefficients or for the analysis spectralcoefficients derived from the analysis spectral coefficients or aninteger multiple of it; and means for calculating the scale factor forthe scale factor band by evaluating the predetermined relation betweenthe encoding amplification factor and the scale factor, dissolved afterthe scale factor wherein the calculated greatest common divisor isinserted into the predetermined relation instead of the encodingamplification factor; means for assigning information to the analysistime signal regarding the scale factors that have been used whenquantizing the original time signal on which the analysis time signal isbased.

In accordance with a fourth aspect of the present invention, this objectis achieved by an apparatus for encoding an analysis time signalcomprising audio and/or video data that has been generated by encodingand decoding an original time signal according to an encoding algorithm,wherein the encoding algorithm has a conversion step and a quantizationstep, wherein the conversion step serves to generate a spectralrepresentation of the original time signal comprising original spectralcoefficients by using an encoding block raster, and wherein thequantization step serves to quantize at least part of the originalspectral coefficients or the spectral coefficients derived from theoriginal spectral coefficients by using a quantization step width,wherein the quantization step of the encoding algorithm includesgrouping of the original spectral coefficients into scale factor bands,wherein a scale factor is assigned to each scale factor band, andwherein the quantization step further comprises weighting the originalspectral coefficients in a scale factor band with an encodingamplification factor, wherein the encoding amplification factor is in apredetermined relation to a scale factor for the scale factor band,comprising: means for establishing the encoding block raster underlyingthe analysis time signal; means for converting the analysis time signalinto a spectral representation of the analysis time signal by using theestablished encoding block raster, wherein the spectral representationof the analysis time signal comprises analysis spectral coefficients;means for grouping of analysis spectral coefficients or spectralcoefficients derived from the analysis spectral coefficients in scalefactor bands; and means for at least approximately calculating thegreatest common divisor of the grouped analysis spectral coefficients orthe spectral coefficients derived from the analysis spectralcoefficients in a scale factor band to obtain the quantization stepwidth used in the quantization step for the analysis spectralcoefficients or for the analysis spectral coefficients derived from theanalysis spectral coefficients or an integer multiple of it; and meansfor calculating the scale factor for the scale factor band by evaluatingthe predetermined relation between the encoding amplification factor andthe scale factor dissolved after the scale factor, wherein thecalculated greatest common divisor is inserted into the predeterminedrelation instead of the encoding amplification factor, and means forquantizing the analysis spectral coefficients or the spectralcoefficients derived from the analysis spectral coefficients by usingthe scale factors determined for each spectral coefficient to obtain anencoded analysis time signal.

In accordance with a fifth aspect of the present invention, this objectis achieved by a method for marking an analysis time signal comprisingaudio and/or video data that has been generated by encoding and decodingan original time signal, wherein the encoding algorithm comprises aconversion step and a quantization step, wherein the conversion stepserves to generate a spectral representation of the original time signalcomprising original spectral coefficients by using an encoding blockraster, and wherein the quantization step serves to quantize at leastpart of the original spectral coefficients or spectral coefficientsderived from the original spectral coefficients by using a quantizationstep width, wherein the quantization step of the encoding algorithmincludes grouping of the original spectral coefficients into scalefactor bands, wherein a scale factor is assigned to each scale factorband, and wherein the quantization step further comprises weighting theoriginal spectral coefficients in a scale factor band with an encodingamplification factor, wherein the encoding amplification factor is in apredetermined relation to a scale factor for the scale factor band,comprising: analyzing the analysis time signal with the followingsub-steps: establishing the encoding block raster underlying theanalysis time signal; converting the analysis time signal into aspectral representation of the analysis time signal by using theestablished encoding block raster, wherein the spectral representationof the analysis time signal comprises analysis spectral coefficients;grouping of analysis spectral coefficients or spectral coefficientsderived from the analysis spectral coefficients into scale factor bands;at least approximately calculating the greatest common divisor of thegrouped analysis spectral coefficients or the spectral coefficientsderived from the analysis spectral coefficients in a scale factor bandto obtain the quantization step width used in the quantization step forthe analysis spectral coefficients or for the analysis spectralcoefficients derived from the analysis spectral coefficients or aninteger multiple of it; and calculating the scale factor for the scalefactor band by evaluating the predetermined relation between theencoding amplification factor and the scale factor, dissolved after thescale factor wherein the calculated greatest common divisor is insertedinto the predetermined relation instead of the encoding amplificationfactor; assigning information to the analysis time signal concerning thescale factors used in quantizing the original time signal on which theanalysis time signal is based.

In accordance with a sixth aspect of the present invention, this objectis achieved by a method for encoding an analysis time signal comprisingaudio and/or video data that has been generated by encoding and decodingan original time signal according to an encoding algorithm, wherein theencoding algorithm has a conversion step and a quantization step,wherein the conversion step serves to generate a spectral representationof the original time signal comprising original spectral coefficients byusing an encoding block raster, wherein the quantization step serves toquantize at least part of the original spectral coefficients or spectralcoefficients derived from the original spectral coefficients by using aquantization step width, wherein the quantization step of the encodingalgorithm includes grouping of the original spectral coefficients intoscale factor bands, wherein a scale factor is assigned to each scalefactor band, and wherein the quantization step further comprisesweighting the original spectral coefficients in a scale factor band withan encoding amplification factor, wherein the encoding amplificationfactor is in a predetermined relation to a scale factor for the scalefactor band, comprising: establishing the encoding block rasterunderlying the analysis time signal; converting the analysis time signalinto a spectral representation of the analysis time signal by using theestablished encoding block raster, wherein the spectral representationof the analysis time signal comprises analysis spectral coefficients;grouping of analysis spectral coefficients or of spectral coefficientsderived from the analysis spectral coefficients in scale factor bands;and at least approximately calculating the greatest common divisor ofthe grouped analysis spectral coefficients or the spectral coefficientsderived from the analysis spectral coefficients in a scale factor bandto obtain the quantization step width used in the quantization step forthe analysis spectral coefficients or for the analysis spectralcoefficients derived from the analysis spectral coefficients or aninteger multiple of it; calculating the scale factor for the scalefactor band by evaluating the predetermined relation between theencoding amplification factor and the scale factor, dissolved after thescale factor, wherein the calculated greatest common divisor is insertedinto the predetermined relation instead of the encoding amplificationfactor; and quantizing the analysis spectral coefficients or thespectral coefficients derived from the analysis spectral coefficients byusing the quantization step width determined for each spectralcoefficient to obtain an encoded analysis time signal.

The present invention is based on the finding that an analysis timesignal generated by encoding and decoding an original time signalaccording to an encoding algorithm or, if already present, a spectralrepresentation of any analysis signal, does not have any explicitinformation about the used quantization, but due to the fact thatquantization is a form of lossy encoding still has influences regardingthe parameters that have originally been quantized.

In audio signals, the values, which are normally quantized, are thespectral coefficients generated by transforming the audio signal from atimely representation into a spectral representation. Analogous, invideo signals, the values that are quantized are the location spectralcoefficients, which mean also coefficients that can be generated byconverting a timely representation of the video signal into a spectralrepresentation of the video signal.

Thus, according to the invention, for analyzing the quantizationunderlying the analysis time signal, the encoding block rasterunderlying the analysis time signal will be determined at first. Thisencoding block raster is the block raster used in encoding the originaltime signal according to the encoding algorithm. After that, theanalysis time signal will be converted into a spectral representation byusing the determined encoding block raster to obtain the coefficients,which have been quantized according to the encoding algorithm. It isbest to use the same parameters for the conversion as in the underlyingconversion step. If, however, the analysis signal is already present asa spectral representation, i.e. a plurality of analysis spectralcoefficients of any signal, the steps of determining the encoding blockraster and converting when determining the quantization step width canomitted.

Now the analysis spectral coefficients will be grouped to obtain a groupof at least two analysis spectral coefficients. Inventively, thegreatest common divisor will now be calculated, at least approximately,from these two analysis spectral coefficients. The greatest commondivisor of the two analysis spectral coefficients corresponds already tothe quantization step width or an integer multiple of the quantizationstep width. If the at least two grouped analysis spectral coefficientsdiffer, for example, by only one quantization step width, then thequantization step width can already be calculated directly from merelytwo analysis spectral coefficients. Her, the quantization step width isimmediately equal to the greatest common divisor of the two analysisspectral coefficients.

If the greatest common divisor is calculated from more than two analysisspectral coefficients the probability, that spectral coefficients aretaken into consideration in calculating the greatest common divisor thatare in a corresponding relationship to one another, is increasing. Then,the greatest common divisor of these spectral coefficients will not onlybe an integer multiple of the quantization step width, but corresponddirectly to the quantization step width.

When the quantization step width is known, the scale factors used inencoding can be established—in the example of an audio encoder—by takinginto consideration the relation between scale factor and encodingamplification factor.

Even a non-uniform quantizer “compressing” larger values beforerounding, can be analyzed easily, when the compression characteristiccurve is applied to the analysis spectral coefficients to generatespectral coefficients derived from the analysis spectral coefficients.From these compressed spectral coefficients the greatest common divisorcan be determined.

If, in the case of a modern audio encoding method, such as MPEG-2 Layer3 or MPEG-2 AAC, scale factors are used in quantization for individualscale factor bands, these scale factors can be calculated from thegreatest common divisor of the spectral coefficients of the respectivescale factor band. Further, by evaluating the different scalefactors—they all have to be in an integer raster—a total scaling of theaudio signal can be determined.

If, however, individual scale factors deviate from the integer raster,the actual quantization step width can be calculated afterwards in theindividual scale factor bands. This is the case, when the operation offorming the greatest common divisor has not provided the actualquantization step widths but integer multiples of them.

The inventive method is advantageous in that a quantization can beestablished totally without explicit quantization information in theencoded and re-decoded signal. Thereby, any encoding systems and anyquantization techniques of encoding systems, respectively, can beanalyzed in order to find out why an encoder unknown as such has certainproperties.

It is another advantage, that especially for forensic purposes and forinvestigations about the violation of copyright protection, encodingproperties can be established via an encoded and re-decoded signal, tobe able to draw the conclusion that a piece of music has been encodedwith a certain encoder. Depending on the initial situation, it can thenbe established, whether this encoder has been authorized or whether thisis a case of audio and/or video piracy.

It is another advantage of the inventive concept that anyencoded/decoded signals that are already present on diverse data bankscan be analysed, in order to add information to them regarding thequantization used in the encoder. This information can then be used byanother encoder in the case of tandem encoding, to enable any number ofrepetitions of encoding/decoding operation with no or minimum tandemencoding distortions. This corresponds to the above-mentioned MOLEconcept, wherein a MOLE signal can also be used to carry out any numberof tandem encodings.

It is another advantage of the inventive method that it can be useddirectly to perform a quantization of the audio signal by using theestablished quantization information, since the analysis spectralcoefficients or spectral coefficients derived there from, respectively,are already present. Therefore, a full encoding according to a certainencoding standard becomes possible, without having to calculate apsychoacoustic model and the iteration loops necessary for quantization,respectively. Thus, all quantization information “hidden” in the encodedand re-decoded analysis time signal can be extracted to obtain a newdecoding with as little effort as possible.

BRIEF DESCRIPTION OF THE DRAWINGS

Preferred embodiments of the present invention will be discussed in moredetail below with reference to the accompanying drawings. They show:

FIG. 1 a basic block diagram of an inventive apparatus for analyzing;

FIG. 2 an apparatus for analyzing with consideration of a non-uniformquantization step width;

FIG. 3 an extension of the apparatus of FIG. 2 for calculating scalefactors for scale factor bands;

FIG. 4 an extension of the apparatus of FIG. 3 for evaluating the scalefactors;

FIG. 5 a basic block diagram of an inventive apparatus for markingand/or encoding the analysis time signal;

FIG. 6 a basic block diagram of a known encoder;

FIG. 7 a basic block diagram of a known decoder;

FIG. 8 a block diagram of an audio encoder; and

FIG. 9 a block diagram of an audio decoder.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

With reference to FIG. 6, a timely representation of an audio signal,for example, is fed into an input 60 of the encoding apparatus shown inFIG. 6. The audio signal will be converted from its timelyrepresentation into a spectral representation, for example via ananalysis filter bank (61). The spectral representation of the audiosignal consists of a plurality of spectral coefficients that cover thewhole spectrum up to a maximum frequency, corresponding to the bandwidthof the audio signal. In a block 62, the absolute amount of each spectralcoefficient x is formed, while the sign x (i.e. sign(x)), is output foranother separate treatment. Thus, merely absolute amounts of spectralcoefficients are present at the output of block 62. Thus, it is madesure that all subsequent computing operations and especially thecompression operation indicated in a block 64 will be fed with defined,i.e. positive, input values.

In the example of the MPEG-2 AAC quantization each spectral coefficientin a block 63 will be applied with an encoder amplification factorderived from the scale factor according to the following equation:x _(—) absw=x _(—) abs/([2^(0.25)·(sf−SF_OFFSET))]  (eq. 1)In equation 1 the used variables have the following meaning:

-   -   x_absw: weighted spectral value at the output of block 63;    -   x_abs: absolute amount of a spectral value at the output of        block 62;    -   sf: the scale factor to be transmitted for a scale factor band        in the bit stream; and    -   SF_OffST: a constant having the value 100 for MPEG-2 AAC, for        example.

The amounts of the spectral coefficients weighted in that way will thenbe compressed in a block 64.

Therefore, a function f(x)=x^(a) can be used, wherein in the case ofcompressing the coefficient a is smaller than 1. In other words, thismeans that smaller spectral coefficients will be reduced to less thanlarge spectral coefficients. This compressing has been found to befavourable with audio signals. Analogous, a reversed function with acoefficient a larger than 1 could be used, such that higher spectralcoefficients will be increased as opposed to smaller spectralcoefficients. Such a function could be favourable for other signals thanaudio signals.

The actual quantization takes place in block 65 denoted with round up orround down. The function of the two blocks 64 and 65 can be illustratedin an equation as follows:x_quant=sign(x)·nint[x _(—) absw^a+const]  (eq. 2)

In equation 2, the used symbols have the following meaning:

-   -   x_quant: the quantized spectral coefficients at the output of        block 65;    -   a: the compression parameter of block 64;    -   const: an additive constant that is preferably kept small; and    -   nint: the function “nearest integer”, that causes the rounding        up and rounding down in block 65, respectively.

By the function nint[y], a value y is generally rounded up or down,respectively, to the nearest integer. If y has the value 1.2, forexample, then nint[y] has the value 1. If y, however, has the value 1.6,then the function nint[y] yields the integer 2. Thus, by the functionnint[y], a continuous set of values is mapped to a discrete set ofvalues. In other words, a continuous function becomes a staircasefunction.

Thus, the total quantization step width corresponds to the product ofthe encoder amplification factor and the “distance” from 1 integer tothe next integer. If rounding between one integer and the next higherinteger takes place, the total quantization step width is equal to theencoder amplification factor, since the distance between the integershas the value of 1. Naturally, any quantization functions can be used,which, for example, perform no rounding up or down to the next integer,but to the next integer after that, for example.

By a block 66, connected to block 62, the quantized spectralcoefficients are provided with their sign again for further processing,to obtain sign information from block 62.

Further, in equation 2, the function sign(x) is listed, which means thatthe quantized spectral coefficients are signed again at the output ofblock 66.

In FIG. 7, the case is considered, where the signs of the individualspectral coefficients are not transmitted together with the quantizedspectral coefficients but supplied separately to a block 66, which addsits sign to each absolute amount of a spectral coefficient. The signedquantized spectral coefficients will then be decompressed in a block 67,i.e. undergo an operation inverse to the operation in compressing 64 inFIG. 6.

In an equation, the function of blocks 66 and 67 can be illustrated asfollows:x_invquant=sign(x_quant)·|x_quant|^(1/a)  (eq. 3)

In equation 3, the variable x_invquant means a decompressed spectralcoefficient. This decompressed spectral coefficient will then beweighted with a decoder amplification factor in block 68, whichcorresponds to the encoder amplification factor. This can be expressedby the following equation:x_recon=x_invquant*[2^(0.25*(sf−SF_OFFSET))]  (eq. 4)

From a comparison of equation 1 with equation 4 it becomes clear thatthe same decoder amplification factor is used for multiplying inequation 4 as for the division in equation 1.

When the spectral coefficients present at output 68 have been convertedfrom their spectral representation to their timely representation againby a block 69, an encoded and re-decoded signal is present, which willsubsequently also be referred to as analysis time signal. Theestablishing of the quantization underlying this signal will beexplained below.

Before this will be dealt with in more detail, it should be noted herethat in an encoding with a uniform quantization, e.g. MPEG-1 layer 2,the calculation of the power function will be omitted. In theterminology of FIGS. 6 and 7, this would correspond to a parameter a.

In summary, it can be stated that in FIGS. 6 and 7, an encoding/decodingsystem based on an encoding algorithm having a conversion step forgenerating a spectral representation of a signal (block 61) and aquantization step for quantization spectral coefficients (block 65) isillustrated. If intermediate processing steps are performed, such as inblock 62, 63 and 64, not the spectral coefficients formed by conversionwill be quantized, but the spectral coefficients derived there from.

At the same time, the encoding algorithm determines the decoding stepsreversed for encoding of decompressing (block 67), providing with adecoder amplification factor (block 68), and the reverse conversion froma spectral representation into a timely representation (block 69). Itshould be noted that the decoder shown in FIG. 7—although not shown inFIG. 7—has also means for removing the sign of the quantized spectralcoefficients before block 67 and means for adding the sign after block67, analogous to FIG. 6.

In the following, reference will be made to FIG. 1, to describe aninventive apparatus for analyzing an analysis signal in form of ananalysis time signal or any signal. It should be noted that no detailedrepresentation will be given of the case, where already a somehowobtained spectral representation of the analysis signal is present. Thiscase, however, results automatically from the following description byomitting the steps of determining the encoding block raster andconverting from a timely representation into a spectral representation.

An analysis time signal at the input of the block diagram shown in FIG.1 is generated by encoding an original time signal via an encoder thatis illustrated in FIG. 6, for example, and by decoding the encoded timesignal output by the encoder via a decoder that is illustrated in FIG.7, for example.

When the encoder of FIG. 6 and the decoder of FIG. 7 work optimally, thesubjective auditory sensation of the original time signal and theanalysis time signal will be identical at the output of the decoder,with the example of an audio signal. This requires, however, that thedata reduction introduced by quantization has merely consequences belowthe psychoacoustic masking threshold and is thus inaudible. In otherwords, this means that the quantization noise introduced by quantizationof block 65 (FIG. 6) has a lower energy than preset by thepsychoacoustic masking threshold.

Although this subjective auditory sensation is clear in the case of anoptimum encoder/decoder, the original time signal and the analysis timesignal to be analyzed differ in that the analysis time signal is basedon quantized spectral coefficients, in contrary to the original timesignal.

Inventively, as is shown in FIG. 1, the encoding block raster used inthe conversion step 61 of FIG. 6 will be determined (block 10). Theinformation about the encoding block raster 10 will be used to perform ablockwise conversion of the analysis time signal from its timelyrepresentation to its spectral representation (block 12). At the outputof block 12, analysis spectral coefficients will be present. Theanalysis spectral coefficients will now be grouped (block 14), such thatone group of at least two analysis spectral coefficients will bepresent. In a block 16, the greatest common divisor of this group willbe calculated within the scope of the accuracy of calculation, at leastapproximately. The greatest common divisor will then correspond to thequantization step width, which corresponds to the spectral valuesbelonging to the considered group.

Here, it should be noted that the term “greatest common divisor” has tobe seen in a generalized sense. The greatest common divisor does notnecessarily have to be an integer but can be any real number. This canbe illustrated with the following example. If a spectral coefficient hasthe value 0.6, while the other spectral coefficient has the value 0.9,the greatest common divisor of these two spectral coefficients will be0.3. In this example, the quantization step width is 0.3. The quantizedfirst spectral coefficient has the value 2. The quantized secondspectral coefficient has the value 3.

The spectral values of the group can be illustrated by multiplying aninteger factor with the established quantization step width. Thereby,the integer factor corresponds to the quantized spectral value.

So far, the case was considered, where the greatest common divisor isalready the quantization step width itself and not an integer multipleof it. No integer multiple of the quantization step width but thequantization step width (QSW) itself results when a spectral coefficientof the group is equal to twice the quantization step width and the otherspectral coefficient of the group is equal to three times thequantization step width. These two spectral coefficients are also prime.

If however, spectral coefficients with the same size are grouped, thenthe greatest common divisor of these two spectral coefficients is ofcourse again the spectral coefficient. The quantization step width wouldthen be equal to the two spectral coefficients which would again be,however, an integer multiple of the actual quantization step width.

If, finally, two spectral coefficients are grouped, wherein one of themis equal to twice the quantization step width and the other is equal tofour times the quantization step width, the greatest common divisor willnot be the quantization step width itself but twice the quantizationstep width.

It should be noted that, in actual cases, significantly more spectralcoefficients will be grouped to one group, so that the case where allspectral coefficients in this group have the same size or are such thatthe greatest common divisor of the spectral coefficient does notcorrespond to the actual quantization step width but to an integermultiple of the quantization step width, respectively, is extremelyrare. The procedure in those cases, where this situation is given, willbe explained later.

With reference to FIG. 2, an extension of the concept shown in FIG. 1will be described, such that a non-uniform quantizer will be used, as ithas for example been described with reference to the encoder shown inFIG. 6. For consideration, an evaluation of the grouped analysisspectral coefficients will be carried out, which are preferably groupedinto their scale factor bands in the example of an audio signal. Theevaluation is illustrated in FIG. 2 by a block 18. It is identical tothe compression described in block 64 of FIG. 6. Thereby, spectralcoefficients derived from the analysis spectral coefficients that aregrouped there will be formed, then the greatest common divisor per scalefactor band will be calculated as in FIG. 1, to output the non-uniformquantized spectral values.

In FIG. 2, it can be seen that it does not matter, whether an evaluationis performed first and a grouping afterwards, or if, as is shown in FIG.2, grouping comes first before evaluating.

FIG. 3 shows the case where not only a non-uniform quantization but alsoa scale factor bandwise amplification, for example via block 63 of FIG.6, has been performed. The multiplication of a spectral coefficient withan amplification factor causes a modification of the quantization stepwidth. If the spectral coefficients are weighted with a factor prior torounding up or down, respectively, the quantization step width, withregard to the spectral coefficient before the multiplication, will bemade larger or made smaller with the amplification factor depending onwhether the amplification factor is smaller or larger than 1.

As it has been illustrated with reference to FIG. 6, the scale factor,which is transmitted as side information to a decoded audio signal, doesnot immediately correspond to the amplification factor, but will becalculated from the amplification factor by the following equation.sf=1/0.25·log2 (q^(1/a))+ SF_OFFSET  (eq. 5)

When block 20, shown in FIG. 3, carries out the function of equation 5,the scale factor for this scale factor band can be calculated from thequantization step width underlying a scale factor band. The quantizationstep width corresponds to the greatest common divisor q or an integerfraction of it.

Therefore, finding out the scale factors comprises the step ofcalculating back the compression of the non-uniform quantizationcharacteristic line (block 18 of FIG. 2) and the conversion of thequantization step width into the logarithmic resolution used in theencoder determined by the amplification factor. If the difference of(s−SF_OFFSET)=1, an amplification factor of 2^^(0.25) will result forthe encoder and the decoder, respectively, which corresponds to a valueof 1.5 dB.

The resulting scale factor values are ideally integers, within the scopeof the accuracy of calculation. There are, however, the followingexceptions.

If all values are offset by a constant amount, this will show a scalingof the analysis time signal by the respective factor. If, for example, aconstant OFFSET results across all scale factors of 0.2, i.e. if thescale factors are for example 101.2, 102.2, 103.2, . . . , this willindicate an OFFSET of 0.2. As expected, the scale factors would have tobe 101.0, 102.0, 103.0, . . . in the scope of the accuracy ofcalculation. An OFFSET of 0.2 corresponds to a scaling of 0.2·1.5 dB=0.3dB. A total scaling of the analysis time signal could for example havebeen caused by an attenuation or amplification, respectively, of theoutput signal of the decoder shown in FIG. 7.

If individual certain scale factors differ from the integer raster, thishas its reason in the described ambiguity with regard to obtaining thegreatest common divisor of a group. As it has been explained, thegreatest common divisor of a group can either be the quantization stepwidth directly, or an integer multiple of the quantization step width.

If this case occurs, equation 5 will be carried out with a modifiedgreatest common divisor q_mod=q/n, wherein the parameter n is an integerhigher than 1. This iterative calculation of the scale factor will beperformed until the resulting scale factor lies in the expected integerraster again. Accordingly, the “quantization step width” determined forthis scale factor band will be modified. It will be divided by thefactor established in the iteration where the integer scale factorraster has been achieved, to obtain the actual “base” quantization stepwidth and not its integer multiple. This factor will further be used tocorrect the quantized values upwards by this factor.

This evaluation of scale factors based on the fact that expectedproperties of the scale factors (such as the integer raster) are known,but not the actual scale factors, is illustrated schematically in FIG. 4with a block 22 and a block 24. The block 22 for evaluating the scalefactors obtains all scale factors SF 0, SF 1, SF 2, . . . , SF N of thescale factor bands with the indices 0, 1, 2, . . . , N, on the inputside, in order to find out on the one hand, whether they are offset by aconstant amount and/or to find out on the other hand, whether they arein an integer raster or not.

If they are no longer in the integer raster, the iterative modifying ofthe quantization step width by block 24 will be carried out forrespective scale factors, to obtain modified scale factors and modifiedquantization step widths, respectively, for the corresponding groups.

FIG. 5 shows a block diagram of an inventive apparatus for marking ananalysis time signal and for encoding an analysis time signal,respectively. This apparatus, which can either be used for marking orimmediately for encoding the analysis time signal comprises means 50 foranalyzing the analysis time signal constructed such as it has beenillustrated with reference to FIG. 1 to 4. The output of means 50, as ithas been described with reference to FIG. 1, consists basically of thequantization step width per group of analysis spectral coefficients.This output will be transmitted via a first output 51 of means 54, forassigning the information to the analysis time signal. The analysis timesignal is at an output 53 of means 54, now, however, provided withinformation that enables a simple re-encoding of the analysis timesignal. This information can particularly be the quantization stepwidth, depending on the design of means 50, or, in the case of an audiosignal encoded according to MPEG-2 AAC the scale factors for each scalefactor band as well as the eventually present constant scaling that canbe established by the concept described with reference to FIG. 4.

The information can be assigned to the analysis time signal in any knownway, for example in a header portion of each and of only a few samplesof the analysis time signal, respectively. This header portion will bedefined by a transport channel for the samples of the analysis timesignal, for example in the shape of additional fields either for eachsample or for a group of samples. In principle, the same mechanism as inwriting the MOLE signal can be used.

Means 50 for analyzing the analysis time signal can further be arrangedto output the analysis spectral coefficients themselves via a secondoutput 52. They will then be used together with the information aboutthe quantization in means 55 for quantization the analysis spectralcoefficients.

Means for quantization, illustrated by block 55 in FIG. 5 works suchthat it divides the analysis spectral coefficients of a group by thequantization step width determined for that group, to obtain thequantized analysis spectral coefficients again, which form the analysissignal present at an output 56 of the apparatus shown in FIG. 5. Means55 preferably implements the same functionalities as illustrated inblocks 62 to 66 of FIG. 6. Now, the quantized analysis signal consistsof the quantized spectral coefficients and can, as described withreference to FIG. 8, possibly be supplied to a bit stream multiplexer 57after an entropy encoding. In the case of the described audio encoderexample, the various side information, such as the scale factors, whichare a measure for the used quantization step width in the individualscale factor bands, are supplied to the bit stream multiplexer 57 fromoutput 51 of means 50.

The quantized spectral coefficients of the analysis signal can then, asit has been described with reference to FIG. 8, be entropy encoded andfinally supplied to a bit stream multiplexer to then be stored orre-decoded again, for example.

It should be noted, that an encoding block raster is establishedpractically by chance by the block-oriented encoder that is, forexample, designed as in FIG. 6. This encoding block raster, however, hasan influence on the spectral representation of the signal. Minimumdeviations or encoding block raster offsets can already lead to the factthat the spectral representation of the decoded signal has a totallydifferent appearance as would actually be expected from a spectralrepresentation of the decoded signal, when it is based on the sameencoding block raster than the decoded signal in general.

In the following, several possibilities for determining the encodingblock raster (block 10 of FIG. 1) will be discussed. The encoding blockraster can simply be determined with the mark, for example in the caseof providing a mark in the analysis time signal.

Alternatively, the encoding block raster can also be established withoutexisting information. Therefore, a portion with a determined number oftime discrete samples will be singled out from the analysis time signalpresent as a sequence of time discrete samples, wherein the first sampleof the singled out portion is referred to as output sample. Afterwards,the taken portion with the predetermined number of time discrete sampleswill be converted from its timely representation to a spectralrepresentation. Then, the spectral representation of the portion will beevaluated with regard to a predetermined criterion, to obtain anevaluation result for the portion. If the evaluation result alreadycorresponds to the predetermined criterion, the correct encoding blockraster has been found by chance. However, if this is not the case, aniterative determination is carried out, by singling out a plurality ofportions of the decoded signal beginning at different output samples,and converting and evaluating them. Thus, a plurality of evaluationresults will be obtained.

Finally, the evaluation results will be searched to find out anevaluation result corresponding best to the predetermined criterion.This method is described in more detail in the patent application filedon Jan. 12, 2000, with the title “Device and Method for determining acoding block raster of a decoded signal”.

In data reducing encoding algorithms that are always present when aquantization is carried out, and that are especially present whenpsychoacoustic models or psychooptical models are used, it is known fromthe start that a certain number of spectral coefficients are either setto zero due to a present quantization step width, or are also set tozero due to a psychoacoustic or psychooptic model. Therefore, if aspectral representation of an analysis time signal is obtained, wherethe spectrum has a relatively “smeared” look, i.e. where thus nodetermined number of spectral coefficients is equal to zero, it will beassumed, that the underlying encoding block raster does not correspondto the original block raster.

The evaluation criterion, for example consisting of a determined numberof spectral coefficients being equal to zero, is therefore clearly nolonger fulfilled, already when one sample deviates from originalencoding block rasters. By combining the above-described method fordetermining the encoding block raster and the method for determining thequantization step width, a full analysis of an encoding underlying ananalysis time signal can be achieved.

It should be noted here, that the inventive method can also be used withencoding methods that are constructed in a simpler way, such asISO/MPEG-1/2 layer 1 or layer 2 or the dolby method AC-3. These methodsdiffer from the embodiments described herein in the following aspects,among others.

A uniform quantization is used, i.e. the function f(x)=x^a degeneratesto f(x)=x and a=1, respectively. Accordingly, in the quantization, nosigns will have to be separated and introduced again.

The term “scale factor” is used differently. While in MPEG-2 layer 3 andMPEG-2 AAC the quantized spectral coefficient and the scale factordetermine the quantization step width together, in MPEG-1/2 layer 1 orlayer 2 as well as in dolby AC-3, some sort of floating-pointrepresentation with a mantissa between −1 and +1 and an exponent for thespectral coefficient will be used. Thereby, the exponent corresponds tothe scale factor and the size in bits of the mantissa to the so-calledbit allocation information (BAL information). When the quantizer stepwidth is known, the scale factors and the BAL information can becalculated back.

Finally, in the so-called simpler methods, no entropy encoding will beperformed.

1. Apparatus for analyzing a spectral representation of an analysissignal comprising audio and/or video data that has been generated byencoding and decoding an original signal according to an encodingalgorithm, wherein the encoding algorithm has a quantization step,wherein the quantization step serves to quantize at least part oforiginal spectral coefficients or spectral coefficients derived from theoriginal spectral coefficients of a spectral representation of theoriginal signal by using a quantization step width, wherein thequantization step of the encoding algorithm includes grouping of theoriginal spectral coefficients into scale factor bands, wherein a scalefactor is assigned to each scale factor band, and wherein thequantization step further comprises weighting the original spectralcoefficients in a scale factor band with an encoding amplificationfactor, wherein the encoding amplification factor is in a predeterminedrelation to a scale factor for the scale factor band, comprising: agrouper for grouping analysis spectral coefficients or spectralcoefficients derived from the analysis spectral coefficients of thespectral representation of the analysis signal in scale factor bands; agreatest common divisor calculator for at least approximatelycalculating the greatest common divisor of the grouped analysis spectralcoefficients or the spectral coefficients derived from the analysisspectral coefficients in a scale factor band, to obtain the quantizationstep width used in the quantization step for the analysis spectralcoefficients or for the analysis spectral coefficients derived from theanalysis spectral coefficients or an integer multiple of it; a scalefactor calculator for calculating the scale factor for the scale factorband by evaluating the predetermined relation between the encodingamplification factor and the scale factor, wherein the calculatedgreatest common divisor is used in the predetermined relation instead ofthe encoding amplification factor; and a scale factor evaluator forevaluating the calculated scale factors, wherein in the case where allscale factors deviate from an integer raster by a constant amount, atotal scaling of the analysis time signal to the original time signal bya factor corresponding to the amount is established.
 2. Apparatusaccording to claim 1, wherein the analysis signal goes back to anoriginal analysis time signal, wherein the encoding algorithm furthercomprises a conversion step before the quantization step, wherein theconversion step serves to generate a spectral representation of theoriginal time signal comprising original spectral coefficients, by usingan encoding block raster, the apparatus further comprising: a blockraster establisher for establishing the encoding block raster underlyingthe analysis time signal; a convener for converting the analysis timesignal into a spectral representation of the analysis time signal byusing the established encoding block raster, wherein the spectralrepresentation of the analysis time signal comprises the analysisspectral coefficients.
 3. Apparatus according to claim 1, wherein thequantization step of the encoding algorithm comprises evaluating theoriginal spectral coefficients with an evaluation specification togenerate the spectral coefficients derived from the original spectralcoefficients, the apparatus further comprising: a spectral coefficientsevaluator for evaluating the analysis spectral coefficients with theevaluation specification, to obtain the spectral coefficients derivedfrom the analysis spectral coefficients.
 4. Apparatus according to claim3, wherein the evaluation specification of the spectral coefficientsevaluator is a function f(x)=x^(a), wherein a is smaller than
 1. 5.Apparatus according to claim 1, further comprising: a scale factorevaluator for evaluating calculated scale factors for each scale factorband, wherein in the case of a scale factor deviating from an integerraster the greatest common divisor underlying this scale factor isdivided iteratively by a natural number greater or equal to two, toobtain a modified greatest common divisor, wherein the scale factor iscalculated in each iteration step by using the modified greatest commondivider, and wherein as many iteration steps are performed until allscale factors are present in an integer raster.
 6. Apparatus accordingto claim 1, further comprising: a quantization step evaluator forevaluating the quantization step width for a plurality of groups ofanalysis spectral coefficients for a plurality of groups of analysisspectral coefficients or of spectral coefficients derived from theanalysis spectral coefficients, wherein in the case of differentquantization step width for the groups, the smallest quantization stepwidth is determined as the quantization step width underlying theanalysis time signal.
 7. Apparatus for marking an analysis time signalcomprising audio and/or video data that has been generated by encodingand decoding an original time signal according to an encoding algorithm,wherein the encoding algorithm comprises a conversion step and aquantization step, wherein the conversion step serves to generate aspectral representation of the original time signal comprising originalspectral coefficients by using an encoding block raster, and wherein thequantization step serves to quantize at least part of the originalspectral coefficients or spectral coefficients derived from the originalspectral coefficients by using a quantization step width, wherein thequantization step of the encoding algorithm comprises grouping of theoriginal spectral coefficients in scale factor bands, wherein a scalefactor is associated to each scale factor band, and wherein thequantization step further comprises weighting the original spectralcoefficients in a scale factor band with an encoding amplificationfactor, wherein the encoding amplification factor is in a predeterminedrelation to a scale factor for the scale factor band, comprising; ananalyzer for analyzing the analysis time signal, comprising: a blockraster establisher for establishing the encoding block raster underlyingthe analysis time signal; a converter for converting the analysis timesignal into a spectral representation of the analysis time signal byusing the established encoding block raster, wherein the spectralrepresentation of the analysis time signal comprises analysis spectralcoefficients; a grouper for grouping analysis spectral coefficients orspectral coefficients derived from the analysis spectral coefficients ofthe spectral representation of the analysis signal in the scale factorbands; a greatest common divisor calculator for at least approximatelycalculating the greatest common divisor of the grouped analysis spectralcoefficients or the spectral coefficients derived from the analysisspectral coefficients in a scale factor band, to obtain the quantizationstep width used in the quantization step for the analysis spectralcoefficients or for the analysis spectral coefficients derived from theanalysis spectral coefficients or an integer multiple of it; and a scalefactor calculator for calculating the scale factor for the scale factorband by evaluating the predetermined relation between the encodingamplification factor and the scale factor, wherein the calculatedgreatest common divisor is used in the predetermined relation instead ofthe encoding amplification factor; a scale factor evaluator forevaluating the calculated scale factors, wherein in the case where allscale factors deviate from an integer raster by a constant amount, atotal scaling of the analysis time signal to the original time signal bya factor corresponding to the amount is established; and an assignor forassigning information to the analysis time signal concerning the scalefactors used in quantizing the original time signal on which theanalysis time signal is based.
 8. Apparatus for encoding an analysistime signal comprising audio and/or video data that has been generatedfor encoding and decoding of an original time signal according to anencoding algorithm, wherein the encoding algorithm has a conversion stepand a quantization step, wherein the conversion step serves to generatea spectral representation of the original time signal comprisingoriginal spectral coefficients by using an encoding block raster,wherein the quantization step for quantization serves to quantize atleast part of the original spectral coefficients or spectralcoefficients derived from the original spectral coefficients by using aquantization step width, wherein the quantization step of the encodingalgorithm comprises grouping of the original spectral coefficients inscale factor bands, wherein a scale factor is associated to each scalefactor band, and wherein the quantization step further comprisesweighting the original spectral coefficients in a scale factor band withan encoding amplification factor, wherein the encoding amplificationfactor is in a predetermined relation to a scale factor for the scalefactor band, comprising: a block raster establisher for establishing theencoding block raster underlying the analysis time signal; a converterfor converting the analysis time signal into a spectral representationof the analysis time signal by using the established encoding blockraster, wherein the spectral representation of the analysis time signalcomprises analysis spectral coefficients; a grouper for grouping theanalysis spectral coefficients or the spectral coefficients derived fromthe analysis spectral coefficients in scale factor bands; a greatestcommon divisor calculator for at least approximately calculating thegreatest common divisor of the grouped analysis spectral coefficients orthe spectral coefficients derived from the analysis spectralcoefficients in a scale factor band, to obtain the quantization stepwidth used in the quantization step for the analysis spectralcoefficients or for the analysis spectral coefficients derived from theanalysis spectral coefficients or an integer multiple of it; a scalefactor calculator for calculating the scale factor for the scale factorband by evaluating the predetermined relation between the encodingamplification factor and the scale factor, wherein the calculatedgreatest common divisor is used in the predetermined relation instead ofthe encoding amplification factor; a scale factor evaluator forevaluating the calculated scale factors, wherein in the case where allscale factors deviate from an integer raster by a constant amount, atotal scaling of the analysis time signal to the original time signal bya factor corresponding to the amount is established; and a quantizer forquantizing the analysis spectral coefficients or the spectralcoefficients derived from the analysis spectral coefficients by usingthe established scale factors to obtain an encoded analysis time signal.9. Method for analyzing a spectral representation of an analysis signalcomprising audio and/or video data that has been generated by encodingand decoding an original signal according to an encoding algorithm,wherein the encoding algorithm has a quantization step, wherein thequantization step serves to quantize at least part of the originalspectral coefficients or spectral coefficients derived from the originalspectral coefficients of the spectral representation of the originalsignal by using a quantization step width, wherein the quantization stepof the encoding algorithm comprises grouping the original spectralcoefficients into scale factor bands, wherein a scale factor isassociated to each scale factor band, wherein the quantization stepfurther comprises weighting the original spectral coefficients in ascale factor band with an encoding amplification factor, wherein theencoding amplification factor is in a predetermined relation to a scalefactor for the scale factor band, comprising: grouping of analysisspectral coefficients or spectral coefficients derived from the analysisspectral coefficients of the spectral representation of the analysissignals into scale factor bands; at least approximately calculating thegreatest common divisor of the grouped analysis spectral coefficients orthe spectral coefficients derived from the analysis spectralcoefficients in a scale factor band, to obtain the quantization stepwidth used in the quantization step for the analysis spectralcoefficients or for the analysis spectral coefficients derived from theanalysis spectral coefficients or an integer multiple of it; andcalculating the scale factor for the scale factor band by evaluating thepredetermined relation between the encoding amplification factor and thescale factor, wherein the calculated greatest common divisor is used inthe predetermined relation instead of the encoding amplification factor;and evaluating the calculated scale factors, wherein in the case whereall scale factors deviate from an integer raster by a constant amount, atotal scaling of the analysis time signal to the original time signal bya factor corresponding to the amount is established.
 10. Method formarking an analysis time signal comprising audio and/or video data thathas been generated by encoding and decoding an original time signalaccording to an encoding algorithm, wherein the encoding algorithm has aconversion step and a quantization step, wherein the conversion stepserves to generate a spectral representation of the original time signalcomprising original spectral coefficients by using an encoding blockraster, wherein the quantization step serves to quantize at least partof the original spectral coefficients or the spectral coefficientsderived from the original spectral coefficients by using a quantizationstep width, wherein the quantization step of the encoding algorithmcomprises grouping of the original spectral coefficients into scalefactor bands, wherein one scale factor is associated to each scalefactor band, wherein the quantization step further comprises weightingthe original spectral coefficients in a scale factor band with anencoding amplification factor, wherein the encoding amplification factoris in a predetermined relation to a scale factor for the scale factorband, comprising: analyzing the analysis time signal with the followingsub-steps; establishing the encoding block raster underlying theanalysis time signals converting the analysis time signal into aspectral representation of the analysis time signal by using theestablished encoding block raster, wherein the spectral representationof the analysis time signal comprises analysis spectral coefficients;grouping of analysis spectral coefficients or spectral coefficientsderived from the analysis spectral coefficients of the spectralrepresentation of the analysis signal into scale factor bands; at leastapproximately calculating the highest common divisor of the groupedanalysis spectral coefficients or the spectral coefficients derived fromthe analysis spectral coefficients in a scale factor band, to obtain thequantization step width used in the quantization step for the analysisspectral coefficients or the analysis spectral coefficients derived fromthe analysis spectral coefficients or an integer multiple of it;calculating the scale factor for the scale factor band by evaluating thepredetermined relation between the encoding amplification factor and thescale factor, wherein the calculated greatest common divisor is used inthe predetermined relation instead of the encoding amplification factor;and evaluating the calculated scale factors, wherein in the case whereall scale factors deviate from an integer raster by a constant amount, atotal scaling of the analysis time signal to the original time signal bya factor corresponding to the amount is established; and assigninginformation to the analysis time signal concerning the scale factorsused in quantizing the original time signal on which the analysis timesignal is based.
 11. Method for encoding an analysis time signalcomprising audio and/or video data that has been generated by encodingand decoding an original time signal according to an encoding algorithm,wherein the encoding algorithm has a conversion step and a quantizationstep, wherein the conversion step serves to generate a spectralrepresentation of the original time signal comprising original spectralcoefficients by using an encoding block raster, wherein the quantizationstep serves to quantize at least part of the original spectralcoefficients or the spectral coefficients derived from the originalspectral coefficients by using a quantization step width, wherein thequantization step of the encoding algorithm comprises grouping theoriginal spectral coefficients into scale factor bands, wherein onescale factor is associated to each scale factor band, wherein thequantization step further comprises weighting the original spectralcoefficients in a scale factor band with an encoding amplificationfactor, wherein the encoding amplification factor is in a predeterminedrelation to a scale factor for the scale factor band, comprising:establishing the encoding block raster underlying the analysis timesignal; converting the analysis time signal into a spectralrepresentation of the analysis time signal by using the establishedencoding block raster, wherein the spectral representation of theanalysis time signal comprises analysis spectral coefficients; groupingof the analysis spectral coefficients or the spectral coefficientsderived from the analysis spectral coefficients into scale factor bands;at least approximately calculating the greatest common divisor of thegrouped analysis spectral coefficients or the spectral coefficientsderived from the analysis spectral coefficients in a scale factor band,to obtain the quantization step width used in the quantization step forthe analysis spectral coefficients or for the analysis spectralcoefficients derived from the analysis spectral coefficients or aninteger multiple of it; and calculating the scale factor for the scalefactor band by evaluating the predetermined relation between theencoding amplification factor and the scale factor, wherein thecalculated greatest common divisor is used in the predetermined relationinstead of the encoding amplification factor; evaluating the calculatedscale factors, wherein in the case where all scale factors deviate froman integer raster by a constant amount, a total scaling of the analysistime signal to the original time signal by a factor corresponding to theamount is established; and quantizing the analysis spectral coefficientsor the spectral coefficients derived from the analysis spectralcoefficients by using the predetermined scale factors to obtain anencoded analysis time signal.
 12. Apparatus for analyzing a spectralrepresentation of an analysis signal comprising audio and/or video datathat has been generated by encoding and decoding an original signalaccording to an encoding algorithm, wherein the encoding algorithm has aquantization step, wherein the quantization step serves to quantize atleast part of original spectral coefficients or spectral coefficientsderived from the original spectral coefficients of a spectralrepresentation of the original signal by using a quantization stepwidth, wherein the quantization step of the encoding algorithm includesgrouping of the original spectral coefficients into scale factor bands,wherein a scale factor is assigned to each scale factor band, andwherein the quantization step further comprises weighting the originalspectral coefficients in a scale factor band with an encodingamplification factor, wherein the encoding amplification factor is in apredetermined relation to a scale factor for the scale factor band,comprising: a grouper for grouping analysis spectral coefficients orspectral coefficients derived from the analysis spectral coefficients ofthe spectral representation of the analysis signal in scale factorbands; a greatest common divisor calculator for at least approximatelycalculating the greatest common divisor of the grouped analysis spectralcoefficients or the spectral coefficients derived from the analysisspectral coefficients in a scale factor band, to obtain the quantizationstep width used in the quantization step for the analysis spectralcoefficients or for the analysis spectral coefficients derived from theanalysis spectral coefficients or an integer multiple of it; a scalefactor calculator for calculating the scale factor for the scale factorband by evaluating the predetermined relation between the encodingamplification factor and the scale factor, wherein the calculatedgreatest common divisor is used in the predetermined relation instead ofthe encoding amplification factor; and a scale factor evaluator forevaluating calculated scale factors for each scale factor band, whereinin the case of a scale factor deviating from an integer raster thegreatest common divisor underlying this scale factor is dividediteratively by a natural number greater or equal to two, to obtain amodified greatest common divisor, wherein the scale factor is calculatedin each iteration step by using the modified greatest common divider,and wherein as many iteration steps are performed until all scalefactors are present in an integer raster.